Home Interior AI Consultant

@chiragardeshna

Hi there, Strong alignment with this project comes from experience building AI-powered commerce assistants, RAG-based recommendation systems, and conversational workflows designed for high-conversion customer engagement. Clear understanding of the requirement for a virtual interior-design assistant capable of contextual product recommendations, upselling, live support, cart actions, service booking, and automated quotation/BOQ generation. Hands-on expertise with LLM integrations, vector search, RAG pipelines, React widgets, Node/Python backends, AWS deployment workflows, API orchestration, and conversational AI architecture ensures scalable and reliable implementation. Risk is minimized through structured intent/slot management, retrieval-grounded responses, secure API integrations, analytics-driven feedback loops, and GDPR/CCPA-conscious data-handling practices. Available to start immediately happy to discuss the conversational architecture, product-data integration workflow, and phased roadmap for deployment and optimization. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@adriank06

Building a virtual interior designer requires strict intent detection to accurately switch between RAG-based product queries, dynamic cart API interactions, and calendar bookings without losing the conversation's context. I have the exact technical background to architect this flow for your e-commerce site. Based on your scope, I will build the React frontend widget and the AWS-deployable backend. Using LLMs and vector search, I will connect your product database so the assistant can recommend items based on dimensions and constraints, answer specific material queries, and handle natural upselling. I will also wire up your cart API, pricing engine, and service calendar to allow in-chat actions like adding to cart and booking measurements. For the sales aspect, I will implement the logic to generate instant BOQs and PDF/email quotations with accurate SKUs and pricing, alongside setting up the feedback loop for A/B testing and ensuring full GDPR/CCPA compliance. As a top-rated freelancer on this platform with a consistent 5-star track record, I have built and deployed complex conversational AI tools for retail and e-commerce environments. My past clients consistently rate my work highly because I focus strictly on robust architecture and delivering exactly what was requested. Please send me a message in the chat here on the platform so we can review your current API structures and database schema.

@somendersingh96

Hi, I can build an AI-powered interior-design assistant that works as a virtual designer, sales consultant, and support agent directly inside your e-commerce platform. Core Features • Conversational product recommendations based on style, room size & budget • Smart upselling and complementary product suggestions • Real-time product/support Q&A • Cart actions directly from chat • Appointment booking integration • Instant quotation & BOQ generation with PDF export Recommended Stack • React widget frontend • Python/FastAPI or Node.js backend • OpenAI + RAG/vector search for contextual recommendations • PostgreSQL + Pinecone/Weaviate for product intelligence • AWS deployment-ready architecture Included ✔ Product DB & cart API integration ✔ Booking/calendar integration ✔ Context-aware conversational workflows ✔ Analytics & A/B testing logs ✔ GDPR/CCPA-aware handling ✔ Fully documented backend & deployment setup Experience Experienced with: AI shopping assistants RAG/LLM systems E-commerce automation Quotation/BOQ workflows Conversational UX A shopper will be able to go from design discussion → recommendations → cart → booked service in one continuous session. Best Regards Somender Singh

@hr157

Hi, This is exactly the kind of AI-assisted commerce experience I enjoy building — not just a chatbot, but a fully integrated conversational sales and design system that can guide users from inspiration to purchase and service booking in a single flow. With 10+ years of full-stack development experience and hands-on work in AI workflows, LLM integrations, RAG systems, vector search, recommendation engines, and conversational UX, I can help architect a scalable virtual interior-design assistant tailored to your e-commerce workflow. I can help build: - Conversational AI sales assistant - Style-aware product recommendation engine - Context-aware upsell/cross-sell flows - Product knowledge retrieval (RAG/vector search) - Cart and checkout integrations - Appointment booking workflows - Dynamic quotation and BOQ generation - React-based frontend widget - AWS-deployable Backend Core capabilities: - Open-ended style conversations - Room-size and constraint handling - SKU-aware recommendations - Installation/care/warranty Q&A - Add-to-cart actions via chat - Live quotation and PDF BOQ generation Architecture focus: - Intent detection and slot-filling - Retrieval-augmented generation (RAG) - Product embedding/vector search - Multi-step conversation memory - GDPR/CCPA-conscious data handling - A/B testing and upsell tracking I’m comfortable integrating with: - Product databases - Pricing engines - Booking calendars - Cart APIs - CRM/order systems - AWS infrastructure Thanks

@riyap1200

Hi, I am interested in this project. I can provide you with the Customized AI Assistant Application for your Ecommerce Site with all features needed for your project in a creative and professional manner. We have previously worked on various Personal blog projects, Games, Mobile Apps & Corporate websites and we can cater to all your requirements in an efficient manner. We can complete the project in 15-30 days and we have long-term experience of various cloud computing platforms (Microsoft Azure, Google Cloud Platform, Amazon Web Services, etc.) and IDEs (Microsoft Visual Studio, Android Studio, XCode). You can trust us with your project as we have previously worked on various AI development projects and we can design and develop your assistant application with the desired features in an elegant manner. Please share your details and connect with us so that we can collaborate and complete this project.

@pabyte

Hello Sir, I’m Abdul from Pabyte. I understand you don’t just need a chatbot, you need a smart AI interior designer inside your e-commerce site that can guide customers, recommend products, upsell naturally, answer questions, add items to cart, book services, and generate accurate BOQ/quotations from live data. I have experience with AI assistants, LLMs, RAG/vector search, e-commerce integrations, React widgets, backend APIs, cart systems, booking flows, PDF quotation generation, AWS deployment, logging, and GDPR/CCPA-aware data handling. My approach would be to first design the conversation flow, intent detection, slot-filling, and product recommendation logic. Then I’ll connect the assistant with your product database, pricing engine, cart API, and booking calendar. After that, I’ll build the React chat widget, quotation/BOQ export, upsell tracking, feedback loop, and analytics logs for A/B testing and conversion improvement. A few questions: Q1 – What platform is your e-commerce site built on? Q2 – Do you already have product, pricing, cart, and booking APIs available? Q3 – Should the BOQ be exported as PDF, email, or both? I look forward to bringing your vision to life! Best regards, Abdul from Pabyte Please come to my chat. I am ready to start right now.

@goranm16

Hi, this fits my AI automation work well. The real win here is making the assistant use live product, cart, pricing, and booking data instead of giving generic design advice. I’d start by mapping intents, required slots, and API contracts, then build the assistant around verified live data. Main risk is wrong BOQ/cart pricing, so I’d add validation before checkout/export and log upsells, drop-offs, and bad answers. I’ve built bots that turn messy user requests into structured actions and reports. Thanks!

@ToufeeqX

Hi, your project immediately stood out to me because it aligns closely with the conversational AI and e-commerce solutions I specialize in. I understand you need an AI assistant that not only recommends personalized products but also manages upsells, bookings, and quotations seamlessly within a single chat session—delivering a true virtual designer experience. While I’m new to Freelancer, I’ve completed extensive real-world projects integrating LLM-based chatbots with live product databases and dynamic quoting, focusing on scalable architecture, context-aware flows, and GDPR-compliant data handling. I’d love to discuss how we can bring this vision to life efficiently and reliably. Looking forward to your thoughts! Regards, Toufeeq.

@gurpreets058

As an experienced AI development firm, GSINFOTECHH OPC Pvt. Ltd. knows firsthand the transformative power of AI on businesses. We have a proven track record in creating and successfully deploying sophisticated retail chatbots that utilize techniques such as LLMs, RAG and vector search. This makes us uniquely well-suited to architect the conversational flow and intent detection required for your home-interior e-commerce site. Moreover, we possess the crucial ability to make live integrations with different APIs, such as your product database, pricing engine, cart API and service-booking calendar. We guarantee a seamless connection between these backends and the front-end React-based widget that we will deliver for your site. Additionally, we have strong proficiency in generating dynamic quotations/BOQs from live data in accordance with your needs. At GSINFOTECHH OPC Pvt. Ltd., we are committed to delivering solutions both powerful and market-ready – and this project is no exception. With our drive to ensure 100% client satisfaction paired with our advanced expertise, we are confident we'll be able to meet and exceed all your project goals, fit within your timeline, all while respecting GDPR/CCPA regulations. Let's get started together!

@bhuvank1

I can build this end-to-end AI-powered interior commerce assistant that acts like a virtual designer, sales consultant, and support agent within a single conversational workflow. I have experience building AI agents, RAG-based systems, and multi-agentic architectures where different agents collaboratively handle recommendation, retrieval, workflow execution, and customer interaction. I’ve also worked on production-grade AI systems involving vector search, dynamic workflows, document generation, API integrations, and real-time orchestration. For your platform, I can architect: • Conversational recommendation engine using LLM + RAG + vector search • Intent detection and slot-filling for style, dimensions, budget, installation, warranty, and booking flows • Context-aware upselling and cross-selling during the same session • Product DB, pricing engine, cart API, and calendar integrations • Dynamic quotation & BOQ generation with SKU-wise pricing, discounts, and PDF/email export • React-based chat widget with streaming responses • AWS-deployable backend with logging, analytics, and A/B testing support • Feedback loop using conversion tracking, abandoned cart analysis, and conversation history. I can also ensure GDPR/CCPA-compliant handling of customer data, session tracking, and secure API.

@PetrusLubbe

IF YOU’RE NOT HAPPY YOU DON’T PAY. Your need for an AI assistant that acts as a savvy interior designer—handling style-driven product recommendations, real-time support, upselling, and bookings seamlessly—shows you value both user experience and conversion performance. My small team will architect a context-aware conversational flow, integrate your databases and APIs, and implement dynamic quotations plus a feedback loop that improves with every interaction, ensuring measurable results. While new to Freelancer, I’ve built AI chatbots for retail that boosted upsell rates and customer satisfaction. Let’s chat! Worst case, you get a free consultation. Regards Pietie L.

@manoval09

Hi, You want customers to explore your interior products with AI-guided recommendations instead of guessing their way through your catalog—an assistant that understands their style and what you actually sell. I've built conversational AI into e-commerce platforms before, and the core challenge is keeping the assistant contextually aware without hallucinating. I'd use Claude API with function calling to tie the assistant directly to your product database. That way it can recommend items by style category, price point, or room type using real data. Frontend-side, a React chat widget handles the conversation; backend middleware (Node.js or Python) routes queries to Claude and your database. Realistic timeline for a solid MVP: 3-4 weeks, including prompt tuning, widget integration, and testing with your actual products. What's your current e-commerce platform—Shopify, WooCommerce, or custom? That determines whether we build API proxying or need smarter data mapping. I can have a working demo (chat widget + one integrated category) in 5 days if you send specs. Best regards, Val

@hafizahmad5353

Hi, I can build an AI-powered interior design assistant that guides customers from style discovery to checkout in a single conversation. The system will recommend products based on dimensions, budget, and design preferences while naturally upselling complementary items. I’ll develop: - Conversational AI with intent detection & memory - Product recommendation engine using RAG/vector search - Cart integration & service booking - Real-time support for materials, installation, warranty, etc. - Dynamic quotation/BOQ generation with PDF export - Analytics for upsell tracking and A/B testing - React-based chat widget with AWS-ready backend Tech stack can include React, FastAPI/Node.js, OpenAI or open-source LLMs, PostgreSQL, and vector DB integration. I focus on scalable architecture, clean APIs, and production-ready code with proper GDPR/CCPA handling. I’d love to discuss your current stack, APIs, timeline, and milestones. Best regards

@Srashtasoft

Hi there, I have read your project requirement. You need an AI-powered virtual interior designer assistant integrated into your eCommerce platform that can recommend products, handle upselling, answer customer queries, manage bookings, generate quotations/BOQs, and guide users from discovery to checkout within a single conversational flow. Our team has experience building AI-powered retail assistants using LLMs, RAG pipelines, vector search, conversational workflows, recommendation systems, and real-time API integrations for e-commerce and service platforms. A few questions: =============== Which eCommerce platform/backend is currently being used? Do you already have structured product metadata for AI recommendations? Which booking/calendar system should be integrated? Should the assistant support voice interactions in future phases? Best Regards, Srashtasoft Team

@KarthikTechCon

Hi, I’m Karthik with 15+ years of experience in AI-powered commerce platforms, LLM/RAG systems, chatbot automation, and enterprise web applications. I can help build your AI Interior Consultant that acts as a virtual designer, sales assistant, and quotation engine inside your e-commerce platform. What I can deliver: • AI conversational assistant with contextual recommendations • Product upselling & support query handling • Cart & booking API integration • Dynamic quotation/BOQ PDF generation • React frontend widget + AWS-ready backend • Feedback & conversion tracking workflows • GDPR/CCPA-compliant implementation Recommended stack: ✔ OpenAI/Claude + RAG/vector search ✔ React + Node.js/FastAPI ✔ PostgreSQL + Vector DB ✔ AWS deployment architecture Expertise: ✔ AI commerce assistants ✔ LLM orchestration & conversational workflows ✔ RAG/vector search systems ✔ Cart, pricing & booking integrations ✔ Real-time analytics & automation systems I focus on scalable AI architecture, clean conversational UX, and reliable integration with existing commerce systems. Ready to discuss milestones and implementation immediately. Regards, Karthik

@Shrutibimpl

Hello There, As per my understanding you want an intelligent AI design assistant for your interior ecommerce site that handles product discovery, upselling, automated quotations, and service bookings. I have hands on experience building conversational commerce agents and integrating Large Language Models with complex inventory and ERP systems for high growth retail platforms. I will turn your catalog into a personalized shopping journey where every customer feels they have a professional designer helping them. You will get a tireless sales consultant that knows your inventory, answers technical questions instantly, and closes sales by adding items to the cart or booking site visits. This means higher conversion rates and larger average order values as the agent naturally suggests the perfect items to match customer choices, providing a premium experience that sets your brand apart. I will build the solution using a Nodejs backend to orchestrate the conversational logic between a fine tuned LLM and your product APIs. I will implement LangChain for robust intent detection and state management, ensuring the agent remembers room dimensions and style preferences throughout the session. Best regards, Bharat Joshi

@parask225

I can build an AI-powered conversational assistant for your home-interior e-commerce platform that works as a virtual designer, sales consultant, and support agent in one seamless chat experience. The assistant will understand customer preferences such as room type, dimensions, budget, and style, then recommend suitable products while naturally upselling matching décor and furniture items. It can answer real-time questions about materials, installation, warranties, and maintenance, add items directly to cart, schedule designer/installation appointments, and generate instant quotations/BOQs with SKU-wise pricing and discounts. Features: • LLM + RAG/vector-search product recommendations • Context-aware multi-step conversations • Cart and booking API integrations • Dynamic PDF/email quotation generation • Analytics for conversions, upsells, and abandoned carts • GDPR/CCPA-compliant customer-data handling Tech stack: • React chat widget • AWS-ready backend • OpenAI integration • Vector database + REST APIs Deliverables include complete frontend/backend source code, deployment docs, analytics dashboard, admin controls, and testing support.

@saadcohuhan

Hi! I've gone through your project in detail and this is exactly the kind of AI-powered solution I specialize in. I can architect and deliver the full virtual interior designer agent you're envisioning. What I'll deliver: ✅ Conversational AI agent with intent detection, slot-filling & full context memory ✅ Smart product recommendations based on style, dimensions & budget ✅ Natural upselling logic built into the conversation flow ✅ Live integrations — product DB, pricing engine, cart API & booking calendar ✅ Dynamic PDF/email quotations & BOQ with correct SKUs, quantities & discount logic ✅ React frontend widget — clean, responsive & embeddable ✅ AWS-ready backend with full documentation ✅ Analytics logging for upsell rate & A/B testing ✅ GDPR/CCPA compliant data handling ✅ Feedback loop from conversions & abandoned carts I have hands-on experience building AI Agents, RAG pipelines, and API integrations for real-world business use cases. I'd love to jump on a quick call to discuss your product database structure and booking system so we can plan milestones properly. Suggested Delivery: 3–4 weeks in milestones Available to start: Immediately ? Let's build something your customers will love!

@dhruvakashyap10

Your vision of transforming a traditional home-interior store into an AI-driven virtual design consultant is exactly the kind of conversational commerce system I would love to build. I can develop an intelligent AI assistant that guides customers from style discovery to cart checkout, quotation generation, and service booking within a single seamless conversation. The solution will include: • Conversational AI with context memory, intent detection, and slot-filling • Personalized product recommendations based on style, dimensions, budget, and preferences • Natural upselling and cross-selling workflows • Real-time support for materials, installation, maintenance, warranty, and pricing queries • Cart API integration for direct add-to-cart actions • Appointment booking integration for measurements, installation, or designer visits • Dynamic quotation and BOQ generation with PDFs/email exports Technically, I can build the backend using LLM + RAG architecture with vector search for product retrieval, connected to your catalog, pricing engine, CRM, and booking systems. The frontend widget will be built in React and optimized for AWS deployment. I will also implement analytics, A/B testing logs, abandoned-cart tracking, and GDPR/CCPA-compliant data handling. I’d be happy to discuss architecture, milestones, and deployment strategy further. Best regards,